Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
2Unique collaborators
1/1Semantic Scholar citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2067072140
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Rishika Bhojwani (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
Claim outcomes
- Ai Safety And Ethics: 1 paper
- Consumer Welfare: 1 paper
- Research Productivity: 1 paper
- Adoption Rate: 1 paper
- Decision Quality: 1 paper
- Other: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| Feature-level AI tools—recommendations, chatbots and comparison engines—lift consumer trust and boost purchase intent for electronics, but privacy fears and cognitive costs blunt the gains; transparent, ethical design is therefore a commercial and regulatory priority.semantic_scholar | Rishika Bhojwani provider id |
Fetched 2026-03-15 | 0 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.